The present invention relates in general, to flame-monitoring equipment and, in particular, to a new and useful combustion analyzer which is based on chaos theory analysis.
A key variable in the combustion of fossil fuels, such as oil, gas, or pulverized coal, is the air/fuel (A/F) ratio. The A/F ratio strongly influences not only the efficiency of fuel usage but also the emissions produced during the combustion process (especially NO.sub.x), and also affects the slagging, fouling, and corrosion phenomena occurring in the combustion zone.
In current fossil/fueled steam generator practice, the A/F ratio is controlled based on a measurement of the oxygen and/or carbon monoxide (CO) concentration in the stack gases, taken at a location downstream of the furnace where the actual combustion process takes place. Unfortunately, in the furnaces of multi-burner steam generators, the A/F differs from burner to burner, and varies significantly with location within the flame of any given burner. Since both the combustion efficiency and NO.sub.x generation levels depend on the localized values of the A/F ratio (i.e., the distribution and mixing within each flame) the measurement and control of a global A/F ratio produced by the entire furnace of the steam generator does not insure optimum performance.
The overall burner A/F ratio and its distribution within the flame is currently set for each burner during start-up in a laborious, iterative procedure that is based upon visual observations of the burner flame and which strongly depends on the experience and judgement of the start-up engineer. During subsequent steam generator operation, a large variety of factors can lead to changes in the A/F ratio and its distribution, with concomitant changes in NO.sub.x emissions, combustion efficiency, etc.
Among the factors that can alter the originally set A/F ratio are:
coal pulverizer wear leading to a change in the size distribution of the coal particles; PA1 change in the overall fuel flow rate from the pulverizer; PA1 change in the distribution among burners of the fuel flow; PA1 change in the distribution of fuel within the flame due to erosion/corrosion of the impeller or conical diffuser; PA1 change in the overall air flow rate; PA1 change in the distribution of air among individual burners; and PA1 change in the distribution of air within a given burner due to changes in the positions of air registers.
Flame quality analyzers are known; see U.S. Pat. No. 4,644,173, to Jeffers for an example of one known flame quality analyzer system.
Satisfactory methods for the continuous monitoring of A/F ratio distribution and the contributing factors listed above are not currently available.
Chaos theory has been used in the academic community for some time. Few practical uses of this theory exist, however.
Two references that provide a good history and general background of chaos analysis are: (1) Gleick, Chaos: Making a New Science, Viking Press, New York, 1987, and (2) Stewart, I., Does God Play Dice? The Mathematics of Chaos, Basil Blackwell Inc., New York, 1989. Some good definitive papers on the application of deterministic chaos are (3) Stringer, J., "Is a Fluidized Bed a Chaotic System?," Proceedings of the 10th International Conference on Fluidized Bed Combustion, San Francisco, Calif., Apr. 30-May 3, 1989, Volume 1, pp. 265-272 and (4) Daw, C. S. and Halow, J. S., "Modeling Deterministic Chaos in Gas Fluidized Beds," presented at the American Institute of Chemical Engineers Annual Meeting, Los Angeles, Calif., Nov. 17-22, 1991, and (5) Daw, C. S., Thomas, J. F., and Richards, G. A., "Modeling Deterministic Chaos in Thermal Pulse Combustion," Presented at the Central States Section 1992 Spring Technical Meeting at the Combustion Institute, Apr. 27-28, 1992. Stringer presents a good overview of the terminology associated with deterministic chaos. (6) H. D. I. Abarbanel, et al., in "Computing the Lyapunov Spectrum of a Dynamical System from an Observed Time Series," Physical Review A, Mar. 15, 1991, Volume 43, Number 6, pp. 2787-2806, has developed the mathematical algorithms to reduce and interpret experimental data, as well as to make predictions regarding a system's behavior.